Tobacco associated diseases of the lung, including chronic obstructive pulmonary disease (COPD), are a leading cause of death and a major contributor to health care costs in the United States. COPD cases are traditionally defined using spirometric thresholds of airflow obstruction. While tobacco smoke may initiate these processes, the susceptibility to decline in lung function or other tobacco associated phenotypes is highly variable. Furthermore, accelerated decline in lung function may continue due to mechanisms such as altered immune tolerance which continue after smoking cessation. The variation in the rate of lung function decline in patients with COPD is poorly described. Because disease definitions are based on single lung function measurements compared to population based standards, lung function decline may be significant even in patients with normal lung function studies. By contrast, individuals classified as having abnormal lung function using traditional disease definitions may have physiologic abnormalities reflective of events during childhood or even in utero which are no longer active or progressive. The project's overall goal is to develop a model integrating clinical, demographic, radiologic and physiological parameters and biomarker levels for the prediction of long-term lung function decline in spirometrically normal subjects. The goal will be accomplished by leveraging a large longitudinal cohort (N=1024) of smokers with normal baseline lung function and median long-term follow up of 9 years (range 4 -12). We will define the subjects as cases and controls based on the presence or absence of rapid long-term lung function decline. We will analyze a set of biomarkers selected based on preliminary data in a cohort with 2-year follow-up. We will test our hypotheses that peripheral blood biomarkers (CCP, CRP, IL6, TNF?, PTX3, sFAS, MMP1, TIMP1, TIMP2, TNFRI and TNFRII) are associated with rate of lung function decline and that demographic and clinical characteristics, peripheral protein biomarkers, and other available radiologic and physiologic parameters, in combination, will constitute a powerful set of predictors for rapid lung function decline. Positive results from this study will allow us to define biomarker signatures and other features in spirometrically normal smokers that predict lung function decline. The validated identification strategy will be used for development and testing of interventions in those individuals at risk for rapid decline.